[fx2trt] Make TRTInterpreter don't need concrete tensor as arg (#59948)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59948
1. We have two Interpreters. One for vanilla op and one for acc op. Some of the logic between them are similar and in this diff we extract out the similar logic to a Base Interpreter. This makes any future general feature change could benefit both Interpreters.
2. Make TRT Interpreter not depending on concrete tensor arg. We will use `InputTensorSpec` to create necessary inputs for acc tracer.
3. Add unittests for acc op converter.
Test Plan:
```
buck test mode/opt caffe2/torch/fb/fx2trt:test_linear
buck test mode/opt caffe2/torch/fb/fx2trt:test_batchnorm
buck test mode/opt caffe2/torch/fb/fx2trt:test_convolution
buck test mode/opt caffe2/torch/fb/fx2trt:test_reshape
buck test mode/opt caffe2/torch/fb/fx2trt:test_relu
buck test mode/opt caffe2/torch/fb/fx2trt:test_add
buck test mode/opt caffe2/torch/fb/fx2trt:test_maxpool
```
Reviewed By: jackm321
Differential Revision: D28749682
fbshipit-source-id: 830d845aede7203f6e56eb1c4e6776af197a0fc3
